Estimation of Dependence Between Paired Correlated Failure Times in the Presence of Covariate Measurement Error

DOI10.1111/1467-9868.00407zbMath1063.62136OpenAlexW2092313313MaRDI QIDQ4672183

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Publication date: 29 April 2005

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9868.00407

zbMATH Keywords

proportional hazards modelcensored datacopula modelsbivariate survival modelmismeasured covariatesreplicaction data

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02)

Related Items (3)

Survival model of a parallel system with dependent failures and time varying covariates ⋮ On the inclusion of bivariate marked point processes in graphical models ⋮ Cross-ratio estimation for bivariate failure times with left truncation

Cites Work

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• A two-stage estimator of the dependence parameter for the Clayton-Oakes model
• Analysis of multivariate survival data
• A Risk Set Calibration Method for Failure Time Regression by Using a Covariate Reliability Sample
• Cox Regression with Covariate Measurement Error
• Consistent Functional Methods for Logistic Regression With Errors in Covariates
• Semiparametric Likelihood Estimation in the Clayton–Oakes Failure Time Model

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